Computes false omission rate from a confusion matrix, see confusion.
False omission rate is defined as FN/(FN + TN), where FN are false negatives and
TN are true negatives. If FN + TN = 0, 0 is returned.

Various tools for inferring causal models from observational data. The package
includes an implementation of the temporal Peter-Clark (TPC) algorithm. Petersen, Osler
and Ekstrøm (2021) <doi:10.1093/aje/kwab087>. It also includes general tools
for evaluating differences in adjacency matrices, which can be used for evaluating
performance of causal discovery procedures.

Bjarke Hautop Kristensen

causalDisco

Tools for Causal Discovery on Observational Data

Anne Helby Petersen

Tobias Ellegaard Larsen

Claus Thorn Ekstrøm

FOR function

<dl><dt>confusion</dt>
<dd>Confusion matrix as obtained from confusion</dd></dl>

Arguments

False Omission Rate — FOR

<dl>

<dt>confusion</dt>
<dd>Confusion matrix as obtained from confusion</dd>

</dl>

FOR: False Omission Rate

Description

Usage

Value

Arguments